415975c9-d8a3-41b3-8130-2976d9429638 - samples
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ABSTRACT:
PROVIDER: EGAD00001006986 | EGA |
REPOSITORIES: EGA
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Project description:We designed spike-in controls for cfMeDIP-seq experiments. These spike-in controls mitigate batch effects and allow for absolute quantification of cell-free DNA.
| EGAS00001005069 | EGA
Project description:Synthetic spike-in controls enable sensitive and reproducible cell-free methylome interrogation
| PRJNA699882 | ENA
Project description:Three separate experiments were carried out using MeDIP-seq and cfMeDIP-seq for methylome analysis. For the first experiment, different starting amounts of HCT116 cell line DNA, sheared to mimic cell-free DNA, were analyzed using MeDIP-seq and cfMeDIP-seq. In the second experiment the limit of detection of cfMeDIP-seq was tested using varying dilutions of colorectal cancer cell line DNA (HCT116) with multiple myeloma cell line DNA (MM1.S). For both cell line DNA samples, the DNA was sheared to mimic cell-free DNA. In the final experiment, we tested the enrichment of human ctDNA using cfMeDIP-seq performed on plasma collected from patient-derived xenografts (PDXs) generated in mice from two colorectal cancer patients.
2018-04-01 | GSE79838 | GEO
Project description:Background.The cell-free methylated DNA immunoprecipitation-sequencing (cfMeDIP-seq) method, is adapted to work with low input DNA and with circulating cell-free DNA (cfDNA). This method allowsfor epigenetic profiling from liquid biopsy samples, providing potential information about tissue of origin. Similar to classical immunoprecipitation based enrichment protocols, interpretation requires a referenceor control to draw inference against a composite experimental baseline and against designed standards allowing for cross-experiment comparisons. Methods.To meet the need for a reference control in cfMeDIP-seqexperiments, we designed spike-in controlsand integrated the use of unique molecular index (UMI) to adjust for polymerase chain reaction (PCR)bias, and immunoprecipitation bias caused by the fragment length, G+C content, and CpG density ofthe DNA fragments. This enables for absolute quantification of methylated DNA in picomoles, while retaining epigenomic information that allows for sensitive, tissue-specific detection as well as comparableresults between different experiments. We designed 54 DNA fragments with combinations of methylationstatus (methylated and unmethylated), fragment length in base pair (bp) (80 bp,160 bp,320 bp), G+C content (35%,50%,65%), and fraction of CpGs within a fragment (1/80 bp,1/40 bp,1/20 bp). We checked spike-in control DNA sequence to ensure they had no cross alignment to the human genome and minimized formation of secondary structures to avoid issues with amplification. We carried outcfMeDIP-seq on either solely spike-in DNA fragments, spike-in DNA added to sheared HCT116 genomic DNA or spike-inDNA added tocfDNAfrom acute myeloid leukemia (AML) samples to assess technical and biological biases, determine optimal amount of spike-in DNA required for an experiment and to assess batch effects,respectively. Results. We show thatcfMeDIP-seqenriches for highly methylated regions, with less than 0.01%non-specific binding and preference to high G+C content and CpG fraction DNA fragments. The use of 0.01 ngof spike-in control DNA results in sufficient sequencing reads to adjust for variance due to fragment length,G+C content and CpG fraction without negatively impacting the number of sequencing reads generatedfor each sample. With known amount of each spike-in control, we generated a generalized linear modelthat can absolutely quantify molar amount from read counts while adjusting for fragment length, G+C content, and CpG fraction. Using our spike-in controls, we show that we can greatly mitigate batch effects,reducing batch associated variance in the data to ≤5%of the total variance. Conclusions.The incorporation of spike-in controls allows for easier interpretation of data generated from cfMeDIP-seq and MeDIP-seq experiments when compared to relative read count. Through the use of a generalized linear model tailored to each experiment, molar amount for each genomic region can becalculated, greatly mitigating both biological and technical biases in the data. We have created an Rpackage, spiky, to convert read counts to DNA picomoles while adjusting for fragment length, G+C contentand CpG fraction.
2021-02-16 | GSE166259 | GEO
Project description:Synthetic sequin cDNA spike in controls sequenced on nanopore
| PRJEB33439 | ENA
Project description:Analysis of RNA samples by massive parallel sequencing holds the promise to assay gene expression in both a quantitative and qualitative fashion and therefore allows for digital gene expression (DGE) profiling. We assessed the effect of different experimental approaches by generating small RNA libraries from a biological sample as well as an equimolar pool of synthetic miRNAs and analyzed the results using capillary dideoxy sequencing and next-generation sequencing platforms (Roche/454, AB/SOLiD and Illumina/Solexa). Whereas different sequencing platforms provided highly similar results, large differences in DGE profiles were observed depending on the library preparation method used. Nevertheless, our results indicate that the preferential nature of the library preparation methods is systematic and highly reproducible and we show that DGE is well suited for the quantification of relative expression differences between samples. Keywords: Transcriptome analysis Examination library method on preparation of equimolar pool of miRNAs, three replicates
2009-07-28 | E-GEOD-16372 | biostudies-arrayexpress
Project description:Normalization of RNA sequencing (RNA-seq) data for gene expression comparison is essential to ensure accurate gene expression quantification. It has been argued that samples with large differences in global expression level cannot be properly normalized without spike-in control RNAs, however, spike-in controls are expensive and not yet widely used. Here, we presented a spike-in independent quantitative RNA sequencing (siqRNA-seq) method, which uses reads from genome DNA as an internal reference to quantify gene expression level. We showed that siqRNA-seq profiles gene expression as traditional RNA-seq, but allows to identify different expression genes between samples with distinct mRNA content. We also showed siqRNA-seq enable us to assess the copy number of mRNA per cell without counting cells and adding spike-ins. Thus, siqRNA-seq provides a convenient and versatile means to quantitatively profile the mRNA landscape in cells.
2024-04-08 | GSE223145 | GEO
Project description:Analysis of RNA samples by massive parallel sequencing holds the promise to assay gene expression in both a quantitative and qualitative fashion and therefore allows for digital gene expression (DGE) profiling. We assessed the effect of different experimental approaches by generating small RNA libraries from a biological sample as well as an equimolar pool of synthetic miRNAs and analyzed the results using capillary dideoxy sequencing and next-generation sequencing platforms (Roche/454, AB/SOLiD and Illumina/Solexa). Whereas different sequencing platforms provided highly similar results, large differences in DGE profiles were observed depending on the library preparation method used. Nevertheless, our results indicate that the preferential nature of the library preparation methods is systematic and highly reproducible and we show that DGE is well suited for the quantification of relative expression differences between samples. Keywords: Transcriptome analysis Examination of three different library preparation methods for small RNAs, two replicates per library method
2009-07-28 | E-GEOD-16370 | biostudies-arrayexpress
Project description:Analysis of RNA samples by massive parallel sequencing holds the promise to assay gene expression in both a quantitative and qualitative fashion and therefore allows for digital gene expression (DGE) profiling. We assessed the effect of different experimental approaches by generating small RNA libraries from a biological sample as well as an equimolar pool of synthetic miRNAs and analyzed the results using capillary dideoxy sequencing and next-generation sequencing platforms (Roche/454, AB/SOLiD and Illumina/Solexa). Whereas different sequencing platforms provided highly similar results, large differences in DGE profiles were observed depending on the library preparation method used. Nevertheless, our results indicate that the preferential nature of the library preparation methods is systematic and highly reproducible and we show that DGE is well suited for the quantification of relative expression differences between samples. Keywords: Transcriptome analysis Examination of three different library preparation methods for small RNAs, two replicates per library method
2009-07-28 | E-GEOD-16369 | biostudies-arrayexpress
Project description:Analysis of RNA samples by massive parallel sequencing holds the promise to assay gene expression in both a quantitative and qualitative fashion and therefore allows for digital gene expression (DGE) profiling. We assessed the effect of different experimental approaches by generating small RNA libraries from a biological sample as well as an equimolar pool of synthetic miRNAs and analyzed the results using capillary dideoxy sequencing and next-generation sequencing platforms (Roche/454, AB/SOLiD and Illumina/Solexa). Whereas different sequencing platforms provided highly similar results, large differences in DGE profiles were observed depending on the library preparation method used. Nevertheless, our results indicate that the preferential nature of the library preparation methods is systematic and highly reproducible and we show that DGE is well suited for the quantification of relative expression differences between samples. Keywords: Transcriptome analysis Examination library method on preparation of equimolar pool of miRNAs, three replicates, sequenced on Illumina GA II
2009-07-28 | E-GEOD-16373 | biostudies-arrayexpress